Methods, apparatuses, and systems providing food material delivery and ordering optimization platform services

Abstract

The application provides a method for optimizing food ingredient distribution and ordering platform service, comprising: based on the food ingredient inventory information of a first company, confirming that the first ingredient inventory is the first inventory quantity of the food ingredients stored in the current first company warehouse; setting the first view point after the first base period of the current set point as the first time point, and setting the period from now to the first point; based on the production quantity information of the first food ingredient and the sales quantity information of the first food ingredient, by analyzing the price volatility of the first food ingredient, the first food ingredient unit price of the first food ingredient at the first food ingredient time is predicted to be the first quantity; if the current first food ingredient unit price is determined to be a second amount, the calculation method of the first increase or decrease rate is to divide the second amount by the second amount, and then subtract the second amount from the first amount; the higher the first increase or decrease rate, the higher the first weight in the preset first reference range.

Description

Technical Field

[0001] This invention relates to a technology that provides food delivery and order optimization platform services to stabilize price fluctuations and inventory depletion. Background Technology

[0002] Stores that sell food using ingredients manage the inventory of each ingredient.

[0003] In traditional stores, the quantity of each ingredient must be checked individually, and if it is determined that a food ingredient is insufficient, it must be ordered separately.

[0004] Furthermore, it is difficult to manage the inventory of food ingredients because it determines whether there is a shortage of food ingredients based solely on the amount of food currently stored in the store.

[0005] Therefore, in order to manage food ingredient inventory, it is necessary to implement technologies that predict food price fluctuations and inventory depletion, and to optimize and process food ingredient orders.

[0006] Existing technical documents

[0007] Patent documents

[0008] Patent Document 1: Korean Patent Registration No. 10-2669470

[0009] Patent Document 2: Korean Patent Registration No. 10-2432840

[0010] Patent Document 3: Korean Patent Registration No. 10-2318865

[0011] Patent Document 4: Korean Patent No. 10-2022-0135435 Summary of the Invention

[0012] The problem that the invention aims to solve

[0013] According to one embodiment, the purpose is to provide a method, apparatus, and system for optimizing food delivery and ordering platform services to stabilize price fluctuations and inventory depletion.

[0014] The purpose of this invention is not limited to the above-mentioned purposes, and other purposes not mentioned can be clearly understood from the following description.

[0015] Methods for solving problems

[0016] According to one embodiment, in a method for providing a food ingredient delivery and ordering optimization platform service that stabilizes price fluctuations and addresses inventory depletion, the device performs the following actions: Based on the food ingredient inventory information of a first company, it determines the current inventory level of a first food ingredient stored in the first company's warehouse as a first inventory level; it sets a time point after a preset first base period from the current point to a first time point, and sets a time point from the current point to the first time point; based on the production volume information and sales volume information of the first food ingredient, it predicts the unit price of the first food ingredient at the time of the first food ingredient by analyzing the price volatility of the first food ingredient, which is then set as a first quantity; if the current unit price of the first food ingredient is determined to be a second amount, then a first increase or decrease is performed. The method for calculating the rate of decrease is to divide the second amount by the second amount, and then subtract the second amount from the first amount; the higher the rate of increase or decrease of the first multiple, the higher the first weight is set within the preset first reference range; based on the first company's food usage, as a result of analyzing the possibility of shortage of the first food ingredient, the first food ingredient at the first time is predicted to be in short supply with a first probability; if it is found that the first probability is higher than the preset reference probability, the quantity of the first food ingredient obtained in advance is subtracted from the first inventory, and the first weight is multiplied by the first weight to calculate the quantity of the first demand; and includes the step of sending a notification message recommending the ordering of the first food ingredient to the terminal of the first company in response to the first demand, providing a method for providing food delivery and order optimization platform services to stabilize price fluctuations and inventory depletion.

[0017] The first time point is used to predict the unit price of the first ingredient. The second time point is defined as the period from the present to the first base period before the second time point, and the period from the second time point to the present. The third time point is defined as the period from the second time point to the first base period before the third time point. Based on the production information of the first food ingredient, the output of the first food component produced in the third period is confirmed as the first production volume, and the output of the first food component produced in the second period is confirmed as the second production volume. The first and second outputs are compared to analyze the changes in the output of the first food component. Based on the analysis of the trend of the first food production volume, the expected output of the first food component to be produced in the first period is predicted as the second production volume. The steps for three production volumes are as follows: Based on the sales volume information of the first food ingredient, confirm the sales volume of the first food ingredient sold in the third period as the first sales volume, and confirm the sales volume of the first food ingredient sold in the second period as the second sales volume; compare the first sales volume and the second sales volume to analyze the sales trend of the first food ingredient; based on the analysis results of the sales trend of the first food ingredient, predict the expected sales volume of the first food ingredient as the third sales volume stage in the first period; define the period that is favorable to the production of the first food ingredient in the first period up to period 1-1, and define the period that has an adverse impact on the production of the first food ingredient in the first period up to period 1-2; and define the period that is favorable to the sales of the first food ingredient in the first period up to period 1-2. The periods are set as periods 1-3, and the periods that adversely affect the sales of the first food ingredient within the first period are set as periods 1-4; the number of days in period 1-1 is confirmed as the number of days in period 1-1, the number of days in period 1-2 is confirmed as day 2, the number of days in period 1-3 is confirmed as day 3, the number of days in period 1-4 is confirmed as day 4, and the number of days in period 1-4 is confirmed as day 5; first, the number of days is divided by the fifth day to calculate the first ratio, the number of days in the second day is divided by the fifth day to calculate the second ratio, the number of days in the third day is divided by the fifth day to calculate the third ratio, the number of days in the fourth day is divided by the fifth day to calculate the fourth ratio; the higher the first ratio, the higher the second weight within the preset second reference range, and the second ratio... The higher the value of the third weight, the higher the weight set within the preset third reference range; the higher the third ratio, the higher the value of the fourth weight set within the second reference range; the higher the fourth weight, the higher the weight set within the third reference range; multiply by the third output and the second and third weights to obtain the fourth output; multiply by 3 salesvolumes and the fourth and fifth weights to calculate the fourth sales volume; subtract the fourth output from the fourth sales volume to calculate the first difference; the higher the first difference, the higher the sixth weight set within the preset fourth reference range; multiply the second quantity by the sixth weight, which may include the step of calculating the first quantity.

[0018] The steps for predicting the probability of stockouts for the first food ingredient at the first consumption level are as follows: Based on the usage history of the first company's food ingredients, confirm the consumption of the first food ingredient used in the third period as the first consumption, and confirm the consumption of the first food ingredient used in the second period as the second consumption; compare the first and second consumption levels to analyze the usage trend of the first food ingredient; based on the analysis results of the consumption change trend of the first food ingredient, predict the usage of the first food ingredient expected to be used in the third period; collect and obtain the first post, which is categorized as the first company's post among posts uploaded to SNS via web crawler, according to the upload time period; classify the first post uploaded in the third period into the first post group, and classify the first post uploaded in the second period into the second post group; set the number of posts classified in one post group as the number of First posts, and set the number of posts classified in two post groups as the number of Second posts; subtract the number of the first post from the number of the second post, divide by the number of the first post, and calculate the increase or decrease rate of the second post; the higher the rate of change of the second post, the higher the rate of change in the preset fifth period. Within a reference range, the higher the weight of the seventh item, the better; the first food product identified as using the first food ingredient in food sold by the first company; among posts uploaded to SNS via web crawler, the second post is collected and retrieved according to the upload time period, and this post is categorized as the first food post; the second post uploaded in the third time period is categorized into the third post group, and the second post uploaded during the second period is categorized into the fourth post group; the number of posts categorized in the Third post group is set as the number of the third post, and the number of posts categorized in the Fourth post group is set as the number of the fourth post group. The number of 4 posts; subtract the number of the fourth column from the number of the third column, divide by the number of the third column, and calculate the increase / decrease rate of the third column using a single system; the higher the increase of the third column, the higher the weight of the eighth column within the preset sixth reference range; multiply the third usage by the seventh and eighth weights to calculate the fourth usage; subtract the fourth usage from the first inventory, and calculate the difference; the higher the number of the second difference, the higher the ninth weight is set within the preset seventh reference range; and subtract the ninth weight from 100%, which may include the step of calculating the first probability.

[0019] Invention Effects

[0020] For example, by predicting price changes and inventory depletion of food ingredients, and optimizing and processing food ingredient orders based on the prediction results, the efficiency of food ingredient inventory management can be improved.

[0021] On the other hand, the effects of the embodiments are not limited to those described above, and other unmentioned effects can be clearly understood by those skilled in the art from the following description. Attached Figure Description

[0022] Figure 1 It is a diagram that outlines the system configuration based on the diaphragm.

[0023] Figure 2 It is a flowchart illustrating the process of providing food ingredient distribution and ordering optimization platform services to stabilize price fluctuations and inventory depletion, based on routine implementation practices.

[0024] Figures 3 to 5 This is a flowchart illustrating the process of predicting the unit price of food ingredients based on a routine implementation.

[0025] Figures 6 to 7 This is a flowchart illustrating the process of predicting the probability of food shortages based on daily implementation examples.

[0026] Figure 8 It is a flowchart illustrating the process of adjusting the required amount of food based on the condition of the stored food in a typical implementation.

[0027] Figures 9 to 10 This is a flowchart illustrating the process of displaying the layout and inventory status based on a typical implementation.

[0028] Figure 11 This is a preliminary schematic diagram of the device configuration according to an embodiment. Detailed Implementation

[0029] The embodiments are described in detail below with reference to the accompanying drawings. However, various modifications can be made to the embodiments, and therefore the scope of the patent application is not limited to or restricted by these embodiments. Any changes, equivalents, or substitutions to the embodiments should be understood to be included within the scope of the claims.

[0030] The specific structural or functional descriptions of the embodiments are provided for illustrative purposes only and may be modified and implemented in various forms. Therefore, the embodiments are not limited to a particular form of disclosure, and the scope of this specification includes changes, uniformities, or substitutions incorporated into the descriptive concepts.

[0031] Terms such as first or second can be used to describe various components, but the interpretation of these terms should only be used to distinguish one component from another. For example, the first component can be named the second component, and similarly, the second component can be named the first component.

[0032] When a component is said to be "connected" to another component, it should be understood that it may be directly connected to or connected to another component, but there may be another component between them.

[0033] The terminology used in the embodiments is for illustrative purposes only and should not be construed as restrictive. Singular expressions include plural expressions unless the context clearly implies otherwise. In this specification, the terms "comprising" or "having" should be understood to mean the presence of the functions, numbers, steps, actions, components, parts, or combinations thereof described herein, and should not exclude the presence or addition of one or more other functions or numbers, steps, actions, components, parts, or combinations thereof.

[0034] Unless otherwise defined, all terms used herein, including technical or scientific terms, shall have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiments pertain. Terms such as those defined in common dictionaries shall be interpreted as having the meaning consistent with their meaning in the relevant descriptive context and shall not be interpreted in an idealistic or overly formal sense unless expressly defined herein.

[0035] Furthermore, when describing the accompanying drawings, regardless of the drawing code, the same reference numerals should be assigned to the same elements, and identical repetitive descriptions should be omitted. When describing embodiments, detailed descriptions should be omitted if it is determined that a specific description of the relevant technical notifications may unnecessarily obscure the essential points of the embodiment.

[0036] The embodiments can be implemented in various types of products, including personal computers, laptops, tablets, smartphones, televisions, smart home appliances, smart cars, kiosks, and wearable devices.

[0037] Figure 1 It is a diagram that outlines the system configuration based on the diaphragm.

[0038] Reference Figure 1 According to one embodiment, the system may include multiple enterprise terminals 100 and devices 200, which can communicate with each other through a communication network.

[0039] First, regardless of whether the communication method is wired or wireless, a communication network can be configured and implemented in various forms to enable communication between servers and between servers and terminals.

[0040] Each of the plurality of manufacturer terminals 100 can be implemented as a computing device with communication functions, such as, but not limited to, mobile phones, desktop PCs, laptops, tablets, smartphones, POS terminals, etc., and can be implemented as various types of communication devices that can connect to external servers.

[0041] The plural company terminal 100 refers to the terminal used by companies that sell food using food ingredients, and may include the first company terminal 110 used by the first company, the second company terminal 120 used by the second company, and so on.

[0042] For ease of explanation below, the operation of the first manufacturer's terminal 110 will be described in detail, but of course the operation of the first company's terminal 110 can be performed in other manufacturers' terminals (such as the second company's terminal 120).

[0043] Each of the multiple manufacturers' terminals 100 can access device 200 through a webpage, application, or other means provided by device 200. Therefore, an application providing food ingredient distribution and order optimization management services can be installed in each of the multiple company terminals 100. This application can operate in conjunction with device 200.

[0044] Device 200 may be its own server, owned by an individual or organization using services provided by device 200, or it may be a cloud server, or it may be a peer-to-peer (P2P) collection of distributed nodes. Device 200 may be configured to perform all or part of the computing, storage / reference, input / output, and control functions of a conventional computer.

[0045] The device 200 can be configured to communicate with multiple vendor terminals 100 via wired or wireless communication, and can control the operation of each of the vendor terminals 100 and control which information is displayed on each of the vendor terminals 100.

[0046] Device No. 200 is implemented as a server, providing food delivery and order optimization management services to stabilize price fluctuations and prevent inventory depletion, and can provide platform services for food delivery and order optimization.

[0047] On the other hand, for ease of explanation, in Figure 1 The image shows only the first company terminal 110 and the second company terminal 120 among the multiple company terminals 100, but the number of terminals may vary depending on the embodiment. There is no particular limitation on the number of terminals as long as the processing power of the device 200 allows.

[0048] Figure 2 It is a flowchart illustrating the process of providing food ingredient distribution and ordering optimization platform services to stabilize price fluctuations and inventory depletion, based on routine implementation practices.

[0049] Reference Figure 2 First, in step S201, the device 200 can determine the inventory quantity of the first ingredient in the first company's warehouse based on the first company's ingredient inventory information.

[0050] According to one embodiment, the database of device 200 stores food ingredient inventory information categorized by company. This inventory information may include product name, production date, and inventory quantity. If, even for the same product, the manufacturing dates differ, it can be managed separately based on the manufacturing date. Therefore, device 200 can track new arrivals or usage of food ingredients in the first company's warehouse and update the first company's food ingredient inventory information in real time. For this purpose, the food ingredients used by the first company are labeled with barcodes, and management can be achieved by tracking the receipt and use of food ingredients through barcode identification.

[0051] For example, if the first food, the second food, the third food, etc. are stored in the warehouse of the first company, the equipment 200 can check the quantity of food ingredients currently stored in the warehouse of the first company based on the food ingredient inventory information of the first company. If the inventory of the first food ingredient is 30 units, then the inventory of the second food ingredient is 50 units, and the inventory of the third food ingredient is 40 units, then 30 can be identified as the first quantity.

[0052] In step S202, device 200 can set a point after a first reference period from the current point to the first time point, and a first time point from the current point to the first time point. Here, the first reference period can be set differently depending on the embodiment, for example, one week.

[0053] In step S203, the device 200 analyzes the price fluctuation of the first food ingredient based on the production volume information and sales volume information of the first food ingredient, and can predict the unit price of the first food ingredient at a first time as the first quantity. Here, the unit price can be expressed as the price of each basic unit set for each food ingredient, and the basic unit can be set according to the characteristics of the food ingredient (e.g., box, bundling, counting, etc.).

[0054] According to the daily embodiment, the database of device 200 stores production information divided by food quantities. Production information indicates how much food has been produced over a period of time and may include information about production quantities, showing how much food has been produced based on different periods such as days, weeks, months, and quarters. In this case, the production information may only include production information for a predetermined period, such as production information over the past five years, or it may only include information about the production quantities being produced in a specific region. For example, the production quantity information for a first food ingredient may include historical production information of the first food ingredient produced in a first region over the past five years.

[0055] In one embodiment, the database of device 200 stores sales volume information categorized by food ingredients. The sales list information indicates how much of the food ingredients have been sold within a certain period, and may include sales volume information indicating how much of the food ingredients have been sold within a certain period based on different timeframes such as days, weeks, months, and quarters. In this case, the sales volume information may only include sales information for a predetermined time period, such as the past 5 years. It may only include information about sales in a specific region. For example, sales information for a first food ingredient might include sales information for the first ingredient sold in a first region over a certain period within the past five years.

[0056] In other words, the device 200 determines the periodic production volume of the first food component based on the production volume information of the first food component, determines the periodic sales volume of the first food component based on the sales volume information of the first food component, and analyzes the price volatility of the first food component based on the periodic production and periodic sales volume of the first food component. As a result of the price volatility of the first food component, the unit price of the first food component can be predicted as the first amount. Figures 3 to 5 The process of estimating the unit price of food ingredients will be explained in detail.

[0057] In step S204, if the current unit price of the first food ingredient is determined to be the second quantity, the device 200 can calculate the first rate of increase or decrease by subtracting the second quantity from the first quantity and dividing by the second quantity. At this time, the second quantity can be confirmed using real-time price information of the first food ingredient, and real-time price information of the first food ingredient can be obtained from an external server or database. Here, the first rate of increase or decrease may refer to the rate of increase or decrease in the unit price of the first food ingredient during the first period from now to the first point in time.

[0058] For example, if the first amount is 110 won and the second amount is 100 won, then device 200 can calculate the first increase or decrease rate as 10% to ((110-100) / 100).

[0059] Furthermore, if the first amount is 90 won and the second amount is 100 won, then the device 200 can calculate the first increase or decrease rate as -10% by ((90-100) / 100).

[0060] In step S205, the device 200 may set the first weight to a higher value within a first reference range that has a higher rate of increase or decrease. Here, the first reference range may be set differently depending on the embodiment, for example, within a range of 0 to 2.

[0061] For example, if the first increment is found to be -10%, device 200 can set the first weight to 0.9; if the first decrease is found to be 0%, the first weight can be set to 1; and if the first increment rate is determined to be 10%, the first weight can be set to 1.1.

[0062] In step S206, the device 200 analyzes the possibility of a shortage of the first food ingredient based on the usage history of the first company's food ingredients, and can predict the probability of a shortage of the first food ingredient at the first time based on the first probability.

[0063] According to one embodiment, the database of device 200 stores the usage history of food ingredients divided by company. The usage history of food ingredients is the cumulative information on the use of food ingredients after they are shipped from the company's warehouse. It can consist of a list indicating which food ingredients and how much were used within a certain period of time. It can include information such as product name, manufacturing date, usage date and usage status, and the usage history of food ingredients can be updated in real time according to the usage status of the food ingredients.

[0064] In other words, device 200 confirms the regular use of the first food ingredient based on the usage history of the first company's food ingredient, analyzes the probability of the first food ingredient being out of stock based on the regular use of the first food ingredient, and can predict the probability of the first food ingredient being out of stock at the first time as a first probability. A detailed explanation of the process for predicting the probability of food stockouts will follow later. Figures 6 to 7 As described in the text.

[0065] In step S207, the device 200 can determine whether the first probability is higher than the reference probability. Here, the reference probability can be set differently depending on the embodiment, for example, 50%.

[0066] If it is determined that the first probability in step S207 is not higher than the reference probability, it can be performed again after a predetermined time period. In step S201, the process of checking the first list can be performed again.

[0067] If the first probability is found to be higher than the reference probability in step S207, then in step S208, the device 200 can subtract the first inventory from the first food supply and multiply it by the first weight to calculate the first demand. Here, the quantity of the first food ingredient can refer to the quantity of the first food ingredient that should be fixed and stored in the warehouse as much as possible, and can be set differently according to the embodiments. In this case, it can be manually set by the manager of the first company, or it can be automatically set according to the purpose of the first food ingredient.

[0068] For example, if the quantity of the first food ingredient is 100 and the first inventory is 70, then equipment 200 can calculate the first demand quantity by ((100-70)×0.9) (if the first weight identifier is 0.9), and if the first weight identifier is ((100-70)×1.1), then equipment 200 can calculate the first demand quantity as 33 units by (((100-70)1.1).

[0069] In phase S209, device 200 can send a notification message to first company terminal 110, which suggests ordering first food ingredient for first demand.

[0070] Figures 3 to 5 This is a flowchart illustrating the process of predicting the unit price of food ingredients based on a routine implementation.

[0071] Reference Figures 3 to 5 First, in step S301, the device 200 can set the time point from the current point to the second point before the first reference period, and the time period from the second point to the current point as the second viewpoint.

[0072] In step S302, the device 200 can set a time point before the first reference period from the second point to the third time point, and a time point before the third time point from the third point to the second point.

[0073] In other words, device 200 can set each cycle in chronological order, in the order of the third cycle, the second cycle, and the first cycle, at which point the length of each cycle can be set equally to the first reference cycle.

[0074] In step S303, the device 200 can identify the production quantity of the first food produced in the third phase as the first production quantity and the production quantity of the first food produced in the second phase as the second production quantity based on the production information of the first food ingredients.

[0075] In other words, the device 200 can check the production volume of the first food component by period based on the production rate information of the first food component, then summarize and confirm the output of the first food component produced in the third period, and confirm the aggregated output as the first production volume, confirm the production volume of the first food component produced in the second period, and confirm the aggregated output as the second production volume.

[0076] In step S304, the device 200 can analyze the production changes of the first food component by comparing the first and second production volumes.

[0077] In step S305, the device 200 is able to predict the expected production of the first food component during the first period as the third production based on the analysis results of the changes in the production of the first food.

[0078] For example, if the first production is confirmed to be 100 and the second production to be 102, then the first and second productions are compared and analyzed. The production change of the first food component is analyzed as the maintenance of productivity, and it is determined that the production of the first food component is maintained from the third period to the second period. Therefore, the median of the first and second productions can be predicted to be 101 as the third production.

[0079] Furthermore, when the first production rate is confirmed to be 100 and the second production rate is 110, the equipment 200 analyzes the change in the production quantity of the first food component as the result of an increase in output by comparing the first production rate with the second production rate, and determines that the production of the first food component increases from the third period to the second period, and can predict that the third output is 120 more than the second production.

[0080] Furthermore, it was confirmed that the apparatus 200 had a first production of 100 units and a second production of 90 units. As a result of comparing the first and second production volumes, the production volume change trend of the first food component was analyzed as a decrease in output. It was determined that the output of the first food component decreased from the third phase to the second phase, and the third production value was predicted to be 80, which was more than the decrease in the second production.

[0081] In step S306, the device 200 can identify the sales volume of the first food ingredient sold in the second period as the second sales volume based on the sales volume information of the first food ingredient.

[0082] In other words, the device 200 can check the sales volume of the first food ingredient by period based on the sales volume information of the first food ingredient, then summarize and confirm the sales volume of the first food ingredient sold in the third period, and confirm the aggregated sales amount as the first sales volume, confirm it as the sales amount of the first food ingredient sold in the second period, and confirm it as the second sales volume.

[0083] In step S307, the device 200 can analyze the sales volume change trend of the first component by comparing the first and second sales volumes.

[0084] In step S308, the device 200 is able to predict the sales volume of the first food ingredient that is expected to be sold in the first period as the third sales volume based on the analysis results of the sales volume change trend of the first food.

[0085] For example, if the first sales volume of the device 200 is confirmed to be 100 units and the second sales volume is confirmed to be 102 units, then the first sales volume and the second sales volume are compared, and the change in the sales volume of the first food ingredient is analyzed as the maintenance sales volume. The sales volume of the first food ingredient is determined to remain from the third period to the second period, so that the median of the first and second sales volumes, 101, can be predicted as the third sales volume.

[0086] Furthermore, if the first sales volume of equipment 200 is confirmed to be 100 units and the second sales volume is confirmed to be 110 units, then the first sales volume and the second sales volume are compared, and the change in the sales volume of the first food ingredient is analyzed as an increase in sales volume. It is determined that the sales volume of the first food ingredient increases from the third period to the second period, and 120 units can be predicted as the third sales volume, which is higher than the second sales volume.

[0087] Furthermore, if the first sales volume is confirmed to be 100 units and the second sales volume is confirmed to be 90 units, then the first and second sales volumes are compared, and the sales volume of the first food ingredient is analyzed as a decrease in sales. It is determined that the sales volume of the first food ingredient decreases from the third period to the second period. Therefore, it can be predicted that 80 units will be the third sales volume, that is, the sales volume of the second product decreases.

[0088] Following step S308, in step S401, the apparatus 200 can designate a period favorable to the production of the first food ingredient within the first period as period 1-1, and a period adversely affecting the production of the first food ingredient within the first period as period 1-2. Here, a period favorable to the production of the first food ingredient may refer to a period where weather is predicted to have a favorable impact on the production activities of the main food ingredient, for example, a period where sunny weather is predicted. Conversely, a period adversely affecting the production of the first food ingredient may refer to a period where weather is predicted to have an adverse impact on the production activities of the main food ingredient, for example, a period where heavy rain or snow is predicted.

[0089] Specifically, based on weather forecast information, device 200 can check the weather for a first period and set the time period during which the predicted weather will have a positive impact on the production activities of the first food ingredient within the first period as period 1-1, and the time period during which the predicted weather will have a negative impact on the production activities of the first food ingredient within the first period as period 1-2. Here, weather forecast information can be obtained through an external server.

[0090] In step S402, the device 200 can set the period that adversely affects the sales of the first food ingredient as period 1-3, and the period that adversely affects the sales of the first food ingredient as period 1-4. Here, the period that is beneficial to the sales of the first food ingredient may refer to a period that may include a schedule that adversely affects the sales activities of the first food ingredient, such as a period that includes public holidays, public holidays, etc. Furthermore, the period that adversely affects the sales of the first food ingredient may be a period in which a schedule adversely affects the sales activities of the first food ingredient, such as a period that includes school holidays, public holidays, etc.

[0091] In step S403, the device 200 can identify the number of days in cycle 1-1 as the number of days in the first cycle, the number of days in cycle 1-2 as the number of days in the second day, the number of days in cycle 1-3 as the number of days in the third day, the number of days in cycle 1-4 as the number of days in the fourth cycle, and the number of days in the first cycle as the number of days in the fifth day.

[0092] In step S404, device 200 can divide the first day by the fifth day to calculate the first rate, the second day by the fifth day to calculate the second rate, the third day by the fifth day to calculate the third ratio, and the fourth day by the fifth day to calculate the fourth ratio.

[0093] In step S405, the device 200 may set the second weight to a higher value within a second reference range that has a higher first ratio, set the third weight within a third reference range to a higher second ratio, set the third weight within a third reference range to a higher third ratio, and set the fifth weight within a third reference range to a higher fourth ratio. Wherein: depending on the embodiment, the second reference range may have different settings, for example, within the range of 1 to 2. Furthermore, the third reference range may be set differently depending on the embodiment; for example, it may be set within the range of 0 to 1.

[0094] For example, if the first ratio is determined to be 10%, the device 200 can set the second weight to 1.1, and if the first ratio is determined to be 20%, the second weight can be set to 1.2.

[0095] Furthermore, if the second ratio is found to be 10%, the device 200 can set the third weight to 0.9, and if the second ratio is found to be 20%, the third weight can be set to 0.8.

[0096] Furthermore, if the third ratio is found to be 10%, the device 200 can set the fourth weight to 1.1, and if the third ratio is found to be 20%, the fourth weight can be set to 1.2.

[0097] Furthermore, if the fourth ratio is found to be 10%, the device 200 can set the fifth weight to 0.9; if the fourth ratio is found to be 20%, the fifth weight can be set to 0.8.

[0098] After step S405, in step S501, device 200 can generate a fourth generation by multiplying the third generation by the second and third weights.

[0099] For example, if the third production is 100 pieces, the second weight is 1.2, and the third weight is 0.9, then equipment 200 can produce the fourth production by (100 × 1.2 × 0.9) 108 units.

[0100] In step S502, device 200 can multiply the third sales volume by the weights of the fourth and fifth to obtain the fourth sales volume.

[0101] For example, if the third sales volume is 100 units, the fourth has a weight of 1.2, and the fifth has a weight of 0.9, then device 200 can generate a fourth sales volume of 108 units according to (100 × 1.2 × 0.9).

[0102] In step S503, the device 200 can calculate the first difference as the fourth sales volume minus the fourth production volume.

[0103] In step S504, device 200 may set the sixth weight to a higher value that has a larger difference within the fourth reference range. Here, the fourth reference range may be set differently depending on the embodiment, for example, within the range of 0 to 2.

[0104] For example, if the first difference is determined to be -10, then device 200 can set the sixth weight to 0.9; if the first difference is determined to be zero, then the sixth weight can be set to 1; and if the first difference is determined to be 10, then the sixth weight can be set to 1.1.

[0105] In step S505, device 200 can multiply the second quantity by the sixth weight to obtain the first quantity. At this time, the content of the second component can be confirmed by the real-time price information of the first component.

[0106] Figures 6 to 7 This is a flowchart illustrating the process of predicting the probability of food shortages based on daily implementation examples.

[0107] Reference Figures 6 to 7 First, in step S601, the device 200 is able to identify the use of the first food ingredient in the third period as the first use and the use of the first food ingredient in the second period as the second use, based on the first company's food ingredient usage history.

[0108] In other words, the device 200 can check the usage of the first food ingredient by period based on the usage history of the first company's food ingredients, then summarize and confirm the usage of the first food ingredient used in the third period and confirm the collected usage as the first consumption, and confirm the usage of the first food ingredient used in the second period and confirm the collected usage as the second consumption.

[0109] In step S602, the device 200 can analyze the trend of change in the use of the first food ingredient by comparing the first and second uses.

[0110] In step S603, the device 200 is able to predict the amount of the first food ingredient expected to be used in the first period as a third use based on the analysis results of the usage trend of the first food.

[0111] For example, if the first use of device 200 is confirmed to be 100 and the second use is confirmed to be 102, then the first use and the second use are compared, and the change in the use of the first food ingredient is analyzed as the usage amount is maintained. It is determined that the usage amount of the first food ingredient is maintained from the third period to the second period, and the median of the first and second consumptions is 101, which can be predicted as the third use.

[0112] Furthermore, if the first use of the device 200 is confirmed as 100 and the second use as 110, then as a comparison of the results of the first and second uses, the trend of the change in the use of the first food ingredient will be analyzed as an increase in the amount used, and it will be determined that the amount used of the first food ingredient increases from the third period to the second period, and it can be predicted that the third use will be 120 more times than the second use.

[0113] Furthermore, if the first usage is confirmed to be 100 times and the second usage is confirmed to be 90 times, then the first usage and the second usage are compared, and the first usage and the second usage are analyzed as a reduction in usage. It is determined that the consumption of the first food ingredient decreases from the second to the third period, and the value of 80 times that is a further reduction from the second usage can be predicted as the third usage.

[0114] In step S604, device 200 can collect and obtain the first post categorized as originating from the first company from posts uploaded to the SNS via crawling, based on the time period in which the posts were uploaded. Here, crawling is a technique for collecting online disclosed information and including it in an index of search objects. Device 200 collects posts uploaded to the SNS via crawling, and among the collected posts, the first company's post can be categorized as the first post.

[0115] When distinguishing posts from the first company among those uploaded to SNS, device 200 can be identified as the first company's post through analysis of text, images, etc.

[0116] For example, if device 200 checks the registered hashtags in a post uploaded to the first user's SNS and finds that the hashtags contain the first company's name, address, etc., then it can identify the post as a post from the first company.

[0117] Furthermore, if device 200 identifies images such as the first company's signboard or menu in a post uploaded to the first user's SNS by examining those images, device 200 can classify the post as belonging to the first company.

[0118] In step S605, device 200 can classify the first post uploaded during the third period into the first post group and classify the first post uploaded during the second period into the second post group.

[0119] In other words, device 200 can check the upload time of each article in the first article and classify the articles in the first article whose third upload time is included in the upload time into the first article group. Articles in the first article that are confirmed to be included in the second upload time can be classified into the second article group.

[0120] In step S606, device 200 can set the number of posts classified as the first post group as the number of first posts, and set the number of posts classified as the second post group as the number of second posts.

[0121] In step S607, device 200 can subtract the number of the second column from the number of the first column and divide by the number of the first column to calculate the second increase rate. Here, the second increase or decrease rate may refer to the ratio of the increase or decrease in the number of positions in the first company from the third period to the second period.

[0122] In step S608, device 200 may set the seventh weight to a higher value within the fifth reference range that has a higher attenuation rate. Here, the fifth reference range may be set differently depending on the embodiment, for example, within the range of 0 to 2.

[0123] For example, if the second increment is found to be -10%, device 200 can set the seventh weight to 0.9%; if the second decrease rate is found to be 0%, the seventh weight can be set to 1; and if the second decrease rate is determined to be 10%, the seventh weight can be set to 1.1.

[0124] Following step S608 and proceeding through step S701, device 200 is able to identify the food sold by the first company as a first food product using a main ingredient. At this point, device 200 can identify the food ingredients used in each food product sold by the first company based on the first company's food information, and then identify the food product using the first food ingredient as the first food product. Here, the food information of the first company can be obtained through an external server or database.

[0125] In step S702, device 200 is able to collect and obtain the second post categorized as the first food from posts uploaded to SNS via web crawling, according to the upload time period.

[0126] Device 200 can distinguish between posts about the first meal and posts uploaded to social networking sites by analyzing text, images, etc.

[0127] For example, if device 200 checks the registered hashtags in a post uploaded to the first user's SNS and finds that the hashtag contains the name of the first food, then it can identify the post as the first food post.

[0128] Furthermore, if the device 200 identifies the presence of the first food in an image by examining a post uploaded to the first user's SNS, the post can be classified as a post containing the first food.

[0129] In step S703, device 200 can classify the second post uploaded in the third time period into a third post group and classify the second post uploaded in the second time period into a fourth post group.

[0130] In other words, device 200 can check the upload time of each post that is divided into the second post, classify the posts that are found to be contained in the third period of the second post, and classify the posts that are found to be contained in the second period of the second post into the fourth group of posts.

[0131] In step S704, device 200 can set the number of posts classified as the third post group to the number of third posts, and set the number of posts classified as the fourth post group to the number of fourth posts.

[0132] In step S705, device 200 can subtract the number of fourth columns from the number of third columns and divide by the number of third columns to calculate the third increase rate. Here, the third increase or decrease rate may refer to the ratio of the increase or decrease of food from the third period to the number of posts of the first food.

[0133] In step S706, device 200 may set the eighth weight to a higher value within the sixth reference range, and have a higher rate of increase or decrease within the third reference range. Here, the sixth reference range may be set differently depending on the embodiment, for example, within the range of 0 to 2.

[0134] For example, if the third increment rate is found to be -10%, then device 200 can set the eighth weight to 0.9%; if the third decrease rate is determined to be 0%, then the eighth weight can be set to 1; and if the third decrease rate is determined to be 10%, then the eighth weight can be set to 1.1.

[0135] In step S707, device 200 can multiply the third usage amount by the seventh and eighth weights to obtain the fourth usage amount.

[0136] For example, if the third usage is 100, the seventh usage has a weight of 1.2, and the eighth usage has a weight of 0.9, then device 200 can calculate the fourth usage as 108 (100 × 1.2 × 0.9).

[0137] In step S708, device 200 can generate a second difference because the first inventory is reduced by the fourth use.

[0138] In step S709, the device 200 can set the ninth weight to a higher value within the seventh reference range as the second difference amount increases. Here, the seventh reference range can be set differently depending on the embodiment, for example, within a range of 0% to 100%.

[0139] For example, if the second difference is determined to be -10, device 200 can set the ninth weight to 40%; if the second difference is determined to be zero, the ninth weight can be set to 50%; and if the second difference is determined to be 10, the ninth weight can be set to 60%.

[0140] At step S710, device 200 can generate a first probability, minus 100% of the ninth weight.

[0141] For example, device 200 can calculate the second difference as -10, set the ninth weight to 40%, and then (100-40), the first inventory as 100, the fourth use as 110, to calculate the first probability as 60%.

[0142] Furthermore, if the first inventory is 100, the fourth usage is 90 units, and the ninth weight is set to 60%, then device 200 can calculate the second difference as 10 units, and the first probability is (100-60), so the first probability can be calculated as 40%.

[0143] Figure 8 It is a flowchart illustrating the process of adjusting the required amount of food based on the condition of the stored food in a typical implementation.

[0144] According to one embodiment, Figure 8 Each step shown can be performed between steps S208 and S209.

[0145] refer to Figure 8First, in step S801, the device 200 can confirm that the expiration date of the first food ingredient is set from the production date to a second reference period. At this time, the device 200 can confirm that, based on the first food ingredient information, the expiration date of the first food ingredient is set within a second reference period from the manufacturing date. Here, the main food ingredient information can be obtained from the device 200's database or an external server.

[0146] In step S802, the device 200 can group the first food ingredients stored in the first company warehouse according to their production date and classify them into multiple food ingredient groups.

[0147] In other words, the device 200 can identify the first food ingredient stored in the first company's warehouse based on the first company's food ingredient inventory information by the production date, and divide the first food ingredient into multiple groups according to the production date.

[0148] In step S803, the device 200 can set the food ingredient group with the slowest manufacturing date among multiple food ingredient groups as the first food ingredient group.

[0149] For example, if device 200 classifies 10 of the 100 food ingredients stored in the first company's warehouse with a confirmed manufacturing date of January 1st into one food ingredient group, classifies 30 of the first ingredients with a confirmed production date of January 11th into another food ingredient group, and classifies 50 of the first ingredients with a confirmed production date of January 21st into another food ingredient group, then it finds that January 21st is the slowest among the multiple food ingredient groups, and the 50 first ingredients with a confirmed production date of January 12th can be set as the first food ingredient group.

[0150] In step S804, the device 200 can check the manufacturing date of the first food ingredient classified as the first food ingredient group from a fourth viewpoint, and check the inventory of the first food ingredient classified as the first food ingredient group as the second inventory.

[0151] For example, if the first food ingredient with a production date of January 12 is set as the first food ingredient group, the equipment 200 can check January 12 as the fourth viewpoint and identify the 50 items as the second inventory.

[0152] In step S805, device 200 can set the viewpoint after the second reference period from the fourth point to the fifth viewpoint, and set the fourth point from the current point to the fifth viewpoint. At this time, if device 200 compares the current point with the fifth point and confirms that the fifth point is earlier than the current time, it can send a notification message to the first company terminal 110 to inform that the first food ingredient needs to be processed.

[0153] In step S806, the device 200 can determine the number of days in cycle 4 as the number of days in the 6th cycle.

[0154] In step S807, device 200 can set weight 10 to a higher value within the 8 reference range because day 6 is longer. Here, the eighth reference range can be set differently depending on the embodiment, for example, within the range of 1 to 2.

[0155] For example, if day 6 is determined to be day 10, device 200 can set the weight of the 10th day to 1.1, and if day 6 is determined to be day 20, the weight of the 10th day can be set to 1.2.

[0156] In step S808, the device 200 can divide the second blank by the first blank to generate a fifth ratio.

[0157] In step S809, device 200 may set the 11th weight to a higher value within the 9th reference range, and a higher value with a ratio of 5. Here, the 9th reference range may be set differently depending on the embodiment, for example, within the range of 1 to 2.

[0158] For example, if the 5th ratio is determined to be 10%, then device 200 can set the 11th weight to 1.1, and if the 5th ratio is determined to be 20%, then the 11th weight can be set to 1.2.

[0159] In step 145S810, the device 200 can adjust the first demand by multiplying the first demand by the 10th and 11th weights.

[0160] For example, if the first demand is 100, the 10th weight is 1.1, and the 11th weight is 1.2, then device 200 can adjust the first demand from 100 to 132 by (100 × 1.1 × 1.2).

[0161] Figures 9 to 10 This is a flowchart illustrating the process of displaying the layout and inventory status based on a typical implementation.

[0162] According to one embodiment, Figures 9 to 10 Each of the steps shown can be performed after step S209.

[0163] Reference Figures 9 to 10 In step S901, device 200 may receive a request from the first company terminal 110 to provide a page to check the inventory status of food ingredients stored in the first company warehouse.

[0164] In phase S902, device 200 provides a first page 110 to display a floor plan of the first company's warehouse, indicating the inventory status of food ingredients stored in the first company's warehouse, thereby controlling the display of the first page on the screen of the first company's terminal. Here, the first page is a page displaying the floor plan of the first company's warehouse, used to show the inventory status of food ingredients stored in the first company's warehouse. The floor plan of the first company's warehouse can be obtained from the database of device 200 or an external server.

[0165] In step S903, if the warehouse of the first company is divided into multiple areas, and the food ingredients stored in each area are determined, then the device 200 can confirm that the first food ingredient is stored in the first of the multiple areas. At this time, the device 200 can confirm the location and size of the first area based on the floor plan of the first company's warehouse, and confirm that the first area is set as the storage area for the first food ingredient.

[0166] In step S904, device 200 can confirm that the maximum amount of food that can be stored in area 1 is set as the first storage amount. At this time, device 200 can confirm that, based on the floor plan of the first company warehouse, the maximum quantity of the first food ingredient that can be stored in the first area can be set as the first storage amount.

[0167] In step S905, device 200 can divide the first inventory by the first storage quantity and calculate the sixth ratio.

[0168] In step S906, device 200 can set the area of ​​the first page display area 1 as the first area. At this time, the first area can be set to various shapes, such as square, circle, etc.

[0169] In step S907, the device 200 can distinguish region 1-1 by setting the size of region 1-1 at a rate of 6 within the first region, and divide the remaining regions within the first region other than region 1-1 into region 1-2. At this time, regions 1-1 and 1-2 can be distinguished in the same form as the first region.

[0170] Following step S907, in step S1001, the device 200 can calculate the first quantity by dividing the first number of uses by the number of days in the fifth day, and the second quantity by dividing the number of days by the number of days in the fifth day. At this time, the first and second doses can be determined by step S601, and the fifth day can be checked by step S403.

[0171] In step S1002, the device 200 can multiply the first quantity by the first reference value to obtain the third quantity, the second quantity by the second reference value, and the fourth quantity by the second reference value. Here, depending on the embodiment, the first reference value can be set to different settings, and the second reference value can be set to a higher value than the first reference value. For example, the first reference value can be set to 1.1, and the second reference value can be set to 1.2.

[0172] In step S1003, the device 200 can calculate the average value between the third and fourth quantities as the fifth quantity.

[0173] In step S1004, device 200 can calculate the number of days 7 by rounding down the decimal point of the first inventory and dividing by the fifth quantity.

[0174] For example, if the first inventory is 100 units and the fifth quantity is 40 units, then equipment 200 can be calculated as the 7th day by rounding down from the decimal point of (100 / 40) by 2.5.

[0175] In step S1005, the device 200 can divide the number of days by the reference number of days to calculate the ratio of the seventh day. Here, the reference number of days can be set differently depending on the embodiment, for example, 10 days.

[0176] In step S1006, the device 200 can determine whether the seventh ratio is higher than the first reference ratio. Here, the first reference ratio can be set differently depending on the embodiment, for example, 70%.

[0177] If, in step S1006, the seventh ratio is found to be higher than the reference ratio, then in step S1007, the device 200 can be controlled to set the first color display area 1-1 to indicate that the inventory is available. Here, the first color can be preset to indicate that the inventory is available; for example, it can be set to blue.

[0178] If it is found in step S1006 that the seventh ratio is not higher than the first reference rate, then in step S1008, the device 200 can determine whether the seventh ratio is higher than the second reference rate. Here, the second reference rate can be set differently depending on the embodiment, for example, 40%.

[0179] If the seventh ratio is found to be higher than the second reference ratio in step S1008, then in step S1009, the device 200 can be controlled to set a second color to display area 1-1 to indicate that the inventory status is normal. Here, the second color can be set in advance to indicate that the inventory status is normal; for example, it can be set to yellow.

[0180] If it is determined in step S1008 that the seventh ratio is not higher than the second reference ratio, then in step S1010, the device 200 can be controlled to display area 1-1 and a third color can be set to indicate that the inventory is in a shortage state. Here, the third color can be set in advance to indicate that the inventory is in a shortage state; for example, it can be set to red.

[0181] Figure 11 This is a preliminary schematic diagram of the device configuration according to an embodiment.

[0182] An apparatus 200 according to one embodiment includes a processor 210 and a memory 220. The processor 210 may include reference... Figures 1 to 10 At least one device described, or performing the reference Figures 1 to 10 At least one of the methods described above. Individuals or groups using device 200 may provide services related to some or all of the methods described above, see [link to relevant documentation]. Figures 1 to 10 .

[0183] The memory 220 may store information related to the methods described above, or it may store programs that implement the methods described below. The memory 220 may be volatile or non-volatile memory.

[0184] Processor 210 can execute programs and control device 200. The code of the program executed by processor 210 can be stored in memory 220. Device 200 is connected to external devices (e.g., personal computers or networks) via input / output devices (not shown) and can exchange data via wired and wireless communications.

[0185] The above embodiments can be implemented as hardware components, software components, and / or combinations of hardware and software components. For example, the devices, methods, and components described in the embodiments can be implemented using one or more general-purpose or special-purpose computers, such as processors, controllers, arithmetic logic units (ALUs), digital signal processors, microcomputers, field-programmable gate arrays (FPGAs), programmable logic units (PLUs), microprocessors, or any other device capable of executing and responding to instructions. The processing unit can execute an operating system (OS) and one or more software applications running on the operating system. The processing unit can also access, store, manipulate, process, and generate data in response to software execution. For ease of understanding, a processing unit can be described as a single processing unit; however, those skilled in the art will recognize that a processing unit may comprise multiple processing elements and / or various types of processing elements. For example, a processing unit may include multiple processors or a processor and a controller. Furthermore, other processing configurations, such as parallel processors, may be used.

[0186] The method according to this embodiment can be implemented in the form of program instructions, which can be executed and recorded on a computer-readable medium by various computer means. The computer-readable medium can contain program instructions, data files, data structures, etc., alone or in combination. The program commands recorded on the medium can be specifically designed and configured for the embodiment, or they can be known and available to a computer software craftsman. Examples of computer-readable recording media include magnetic media (such as hard disks, floppy disks, and magnetic tapes), optical media (such as CD-ROMs and DVDs), magneto-optical disk media (such as floppy disks), and hardware devices (such as ROMs, RAMs, flash memory, etc.) specifically configured to store and execute program commands. Examples of program instructions include machine code (e.g., code generated by a compiler) and high-level language code (e.g., code executable by a computer using an interpreter). The hardware device can be configured to operate as one or more software modules to perform the operations of the embodiment, and vice versa.

[0187] This software may include computer programs, code, instructions, or one or more combinations thereof, and may configure processing units to operate as intended, or may individually or collectively command processing units. Software and / or data may be permanently or temporarily contained in any type of machine, component, physical device, virtual device, computer storage medium, or apparatus, or in transmitted signal waves, so that processing units may interpret them or provide instructions or data to processing units. This software is distributed on networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

[0188] Although the above embodiments have been described with limited drawings, those skilled in the art can make various technical modifications and alterations based on the above description. For example, appropriate results may be obtained if the described techniques are performed in a different order than the described methods, and / or if the components of the described systems, structures, devices, circuits, etc., are combined or combined in a different manner than the described methods, or are replaced or substituted by other components or equivalents.

[0189] Therefore, other embodiments, other embodiments, and those equivalent to the patent claims also fall within the scope of the claims described below.

Claims

1. A method for a food delivery and order optimization platform service, providing solutions to stabilize price fluctuations and inventory depletion, wherein, include: Based on the food ingredient inventory information of the first company, verify the current inventory of the first food raw material, which is the first inventory quantity; Set the time point from the current point to the first time point after the preset first base period; set the time point from the current point to the first time point. Based on the production volume information and sales volume information of the first food ingredient, by analyzing the price fluctuation of the first food ingredient, the unit price of the first food ingredient at the time of the first food ingredient is predicted to be the first quantity. If the unit price of the first food ingredient is determined to be the second amount, the calculation method for the first increase or decrease rate is to divide the second amount by the second amount and then subtract the second amount from the first amount. The higher the rate of increase or decrease of the first factor, the higher the first weight will be set within the preset first reference range; Based on the first company's food usage, as a result of analyzing the possibility of shortage of the first food ingredient, the probability of shortage of the first food ingredient in the first instance is predicted with the first probability. If the first probability is found to be higher than the preset reference probability, then the quantity of the first food ingredient obtained in advance is subtracted from the first inventory quantity, and the first weight is multiplied by the first weight to calculate the quantity of the first demand; and Send a notification message to the first company terminal, recommending the steps to order the first batch of food ingredients based on the quantity required for the first order.

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